Summary of Double Machine Learning For Adaptive Causal Representation in High-dimensional Data, by Lynda Aouar et al.
Double Machine Learning for Adaptive Causal Representation in High-Dimensional Databy Lynda Aouar, Han YuFirst submitted…
Double Machine Learning for Adaptive Causal Representation in High-Dimensional Databy Lynda Aouar, Han YuFirst submitted…
Trajectory Representation Learning on Road Networks and Grids with Spatio-Temporal Dynamicsby Stefan Schestakov, Simon GottschalkFirst…
EXCON: Extreme Instance-based Contrastive Representation Learning of Severely Imbalanced Multivariate Time Series for Solar Flare…
Multi-Modal Self-Supervised Learning for Surgical Feedback Effectiveness Assessmentby Arushi Gupta, Rafal Kocielnik, Jiayun Wang, Firdavs…
GeomCLIP: Contrastive Geometry-Text Pre-training for Moleculesby Teng Xiao, Chao Cui, Huaisheng Zhu, Vasant G. HonavarFirst…
Learning From Graph-Structured Data: Addressing Design Issues and Exploring Practical Applications in Graph Representation Learningby…
Variational Graph Contrastive Learningby Shifeng Xie, Jhony H. GiraldoFirst submitted to arxiv on: 11 Nov…
An Efficient Memory Module for Graph Few-Shot Class-Incremental Learningby Dong Li, Aijia Zhang, Junqi Gao,…
Bridge: A Unified Framework to Knowledge Graph Completion via Language Models and Knowledge Representationby Qiao…
Shedding Light on Problems with Hyperbolic Graph Learningby Isay Katsman, Anna GilbertFirst submitted to arxiv…